Join

Machine Learning courses

1775 Courses

California Institute of Technology Indian Institute of Technology Roorkee

Fintech: The Future of Finance

The financial industry is evolving rapidly, with technology-driven services leading the way. To stay competitive, finance professionals must develop a strong understanding of technological advancements. Key technologies like AI, machine learning, distributed ledgers, and algorithmic trading are reshaping the sector. Our Financial Technology Prof.
course image
California Institute of Technology edX

Foundations of AI

The world of Artificial Intelligence (AI) is no longer science fiction. It is rapidly permeating across all industries and impacting every aspect of our daily life. Whether you are an industry professional, an executive, an entrepreneur, or a student, developing a foundational understanding of AI and its impact on your organization and our societ.
course image
California Institute of Technology Southern New Hampshire University

AI Agents and Agentic AI with Python & Generative AI

Forget everything you know about traditional AI. Agentic AI doesn’t just analyze data; it acts on it. From drafting sales emails to updating CRMs, it’s not just a tool—it’s a game-changer. Are you ready to harness its power? Agentic AI combines Generative AI with tools and actions, enabling the creation of "agents" that revolutionize how work is.
course image
California Institute of Technology Coursera

DevOps and AI on AWS: AIOps

DevOps and AI on AWS: AIOps | Coursera Enhance your DevOps processes with the power of artificial intelligence in the DevOps and AI on AWS: AIOps course. Dive into applying AI techniques to increase operational efficiency and reduce human intervention in IT operations. Unveil the potential of AIOps to transform your DevOps operations as we scal.
course image
California Institute of Technology Harvard University

Data Science and Machine Learning

Interested in a career in data science and machine learning but unsure where to begin? The demand for professionals skilled in machine learning (ML) and artificial intelligence (AI) is soaring, driven by an ever-evolving data science landscape. As machine learning tools become more widely available, companies are increasingly adopting them, fueling.
course image
California Institute of Technology Harvard University

Python for Data Science and Machine Learning

Have you considered a career in data science and machine learning but didn't know where to begin? The demand for professionals in machine learning (ML) and artificial intelligence (AI) is growing exponentially. With the ever-evolving data science landscape, the need for skilled data science analysts and engineers, especially those proficient in P.
course image
California Institute of Technology Delft University of Technology

AI in Practice

Begin by discovering the various advantages and impacts of AI and culminate with a strategic plan for its implementation. Artificial Intelligence (AI) is emerging as a transformative force, much like electricity was over a century ago. Although the full impact on our lives remains to be seen, organizations must begin considering how to integrate AI.
course image
California Institute of Technology edX

Artificial Intelligence & Machine Learning in Healthcare

Artificial Intelligence & Machine Learning in Healthcare Join this MicroMasters program to discover how Artificial Intelligence (AI) and Machine Learning (ML) are transforming healthcare. Through two self-paced courses, gain insights into improving healthcare with AI and ML. The first course will lay the groundwork for understanding AI and ML,.
course image
California Institute of Technology Delft University of Technology

Data Skills for Artificial Intelligence

Data Skills for Artificial Intelligence Artificial Intelligence and Machine Learning have become integral techniques for most services and products, with data being central to robust and successful AI/ML applications. Without solid data management, AI projects frequently underperform or even fail. This series of MOOCs provides unique insights and.
course image
California Institute of Technology Harvard University

Computer Science for Artificial Intelligence

Computer Science for Artificial Intelligence The demand for expertise in AI and machine learning is growing rapidly. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, AI is transforming how we live, work, and play. This series will enable you to take th.
course image

More and more products are now being developed using artificial intelligence. To avoid being left on the sidelines of progress, managers must understand how the robot’s “brains” work

Artificial intelligence (AI) and machine learning technologies have been used for many years, but now the intensity of their use has increased significantly. For example, machine learning is being actively implemented in telecommunications, retail, marketing and e-commerce. But many still do not fully understand what it is.

Machine learning involves the system processing a large number of examples, during which it identifies patterns and uses them to predict the characteristics of new data. In other words, this is the process of giving AI ml courses “consciousness”, the ability to remember and analyze.

Machine learning use cases

The use of machine learning has touched many areas in our lives. Let's look at the most striking examples of the use of computer intelligence:

Facial recognition in the subway will help identify violators or criminals in a huge mass of people. Ordinary observers cannot cope with this task. But a fast-learning machine will do this job without any problems.

What do you need for machine learning (ML)?

For those interested in training, there are several requirements to be met in order to be successful in this field. So, there are the main points you need to know about the machine learning course. These requirements include:

  1. Basic knowledge of programming languages such as Python, R, Java, JavaScript, etc.

  2. Average knowledge of statistics and probability.

  3. Basic knowledge of linear algebra in the ml course. In a linear regression model, a line is drawn through all the data points, and that line is used to calculate new values.

  4. Understanding Calculus.

  5. Knowledge of how to clean and structure raw data into the desired format to reduce the time required for decision making.

Machine learning courses from AI Eeducation are the best choice!